Fundamentals of Descriptive and Inferential Statistics

📋 Course Outline

1. Data Types
2. Descriptive Statistics
3. Measures of Central Tendency
4. Mean, Median, Mode
5. Measures of Dispersion
6. Range, Variance, SD
7. Data Visualization
8. Sampling Theory
9. Hypothesis Testing
10. Confidence Intervals
11. Statistical Tests
12. t-tests, ANOVA, Chi-Square

📖 1. Data Types

🔑 Key Concepts & Definitions

• Data: Raw facts, figures, or observations collected for analysis, which can be qualitative or quantitative.
• Qualitative Data: Non-numeric data representing categories or qualities, such as colors, labels, or opinions.
• Quantitative Data: Numeric data representing measurable quantities, which can be discrete (countable) or continuous (measurable).
• Discrete Data: Quantitative data with specific, separate values (e.g., number of students).
• Continuous Data: Quantitative data that can take any value within a range (e.g., height, temperature).
• Nominal Data: Categorical data without an intrinsic order (e.g., gender, nationality).
• Ordinal Data: Categorical data with a meaningful order but unequal intervals (e.g., rankings, satisfaction levels).

📝 Essential Points